A new algorithm uses the location ofblasts (red) from improvised explosivedevices to deduce the hiding places ofweapons caches (yellow) in Baghdad.

kind of a case study, expert-opinion sort
of field into a quantitative area,” says
Alexander Gutfraind, a mathematician
at Los Alamos National Laboratory in
New Mexico. “If you have a mathematical
model that can describe the structure
of a terror network—and the model
works — then you can predict the future.”
Some researchers are convinced of
math’s merits but face roadblocks in
persuading other people that calculations can aid the fight. “These days, the
impression I get is that people who ought
to support this kind of research don’t fully
believe that mathematics can be useful,”
says mathematician Jonathan Farley of
Johannes Kepler University Linz in Austria. “And their belief is so extreme that
they’re not even willing to check it out.”
But some of the new methods are
beginning to attract attention. Farley, Gutfraind and others belong to the
Consortium for Mathematical Methods
in Counterterrorism, which promotes
math’s role in tackling counterterrorism and global security problems. Consortium members share methods and
papers, and meet annually to talk about
emerging problems in their field, such as
how to quantify threats of violence, how
to disrupt terror cells and how terrorists
arrange themselves into groups.

Such simple maps can miss crucial features of terrorist networks. “The person
with the most links is not necessarily the
most important person,” Farley says.

Carley’s research group and others have begun to find that people who
have roles in multiple groups — called
interstitial members—are some of
the most important. Interstitial members communicate between groups and
relay information, a position critical
to operations going as planned. A new
technique called fuzzy grouping, which
allows people to be assigned to multiple
groups simultaneously, better describes
how these people fit into networks,
Carley says.

Another important attribute is exclusivity. Some members of a network have
specialized training and so are in high
demand for certain jobs. People who
know how to launder money or fly an airplane, for instance, have a high exclusivity measure. Accounting for exclusivity
measures and adopting fuzzy grouping
techniques can lead to more nuanced
descriptions of covert networks.

Putting terrorists into groups orassigning exclusivity measures is a mat-ter of collecting and assessing the rightpieces of data. “The data is coming from awide variety of sources, things like open-source text, crowd-sourced informationoff the Web, anything you can basicallyimagine,” says Carley. “The million dol-lar question is, can we drill down and findthe network relevant to the problem?”Ideally, drilling down through thisaggregation of data will reveal trails.“We link together the who, the what,the where, the why, the how, and weuse all of these things in a dynamiccomplex configuration,” Carley says.Once specific trails are identified, com-plex grouping algorithms may be ableto decipher unexpected locations forgroups to meet, for instance.

Linked upa type of network arrangement called fuzzy group clustering pinpoints people who
belong to two distinct groups simultaneously, such as Saddam hussein. models suggest that
such “interstitial” members are likely to be the key coordinators of a terrorist mission.

Networks linking Iraqi leaders,
other individuals and mosques

Ibrahim BaghiAbdul AzizIyad AllawiNazar al-Khaizaran

Muhammed Sadr
Muhammed Bakr

Connecting the right dots
In the aftermath of the September 11
attacks, a technique called social network analysis was touted as the best way
to find terrorist kingpins. Connecting the
dots between people called attention to
those who were most highly linked — presumably, the most important members
of the network. “The idea was to disconnect those social networks, and if you did
this, you could inhibit, prevent or moderate the impact of these events — and
maybe actually save lives,” Carley says.
“What we found in the ensuing time is
that taking an approach that focuses only
on social networks will not work.”